Sanmay Das
Teaching Papers Data CV (likely outdated)
Sanmay Professor
Department of Computer Science
George Mason University

Office: ENGR 3619
e-mail: sanmay at gmu dot edu
Phone: 703-993-6820 

Department of Computer Science
George Mason University
4400 University Drive, MSN 4A5
Fairfax, VA 22030


If you are interested in research opportunities, grad school at GMU, or potential postdoc / visitor / intern positions in my group, please read this page before contacting me.


I have broad interests across AI, machine learning, and computational social science. Recently I have worked mainly on designing effective algorithms for agents in complex, uncertain environments, and on understanding the social or collective outcomes of individual behavior. My research spans market microstructure, matching markets, social networks, reinforcement learning, sequential decision-making, supervised learning, and data mining. For more details, you can read some of my papers.

Professional Bio (for talk announcements, etc.)

Sanmay Das is a Professor of Computer Science at George Mason University. He has broad interests across AI, machine learning, and computational social science. His research interests are in designing effective algorithms for agents in complex, uncertain environments, and in understanding the social or collective outcomes of individual behavior. His recent work focuses on algorithmic allocation of scarce societal resources, with an eye towards the distributive justice implications of different policies and mechanisms. Dr. Das is chair of the ACM Special Interest Group on Artificial Intelligence, a member of the board of directors of the International Foundation for Autonomous Agents and Multiagent Systems, and serves as an associate editor of the ACM Transactions on Economics and Computation and of the Journal of Artificial Intelligence Research. Dr. Das has served as program co-chair of the AAMAS and AMMA conferences and area chair for AAAI, in addition to regularly serving as a senior program committee member of major conferences including IJCAI, AAAI, EC, and AAMAS. He has been recognized with awards for research and teaching, including an NSF CAREER Award and the Department Chair Award for Outstanding Teaching at Washington University. He has worked with the US Treasury department on machine learning approaches to credit risk analysis, and occasionally consults in the areas of technology and finance. He holds a Ph.D. from MIT, and a Bachelor's degree from Harvard.

Selected Audio/Video and Media Coverage

  • One benefit of Zoom talks is that people record them! Some recent recorded talks can give you a flavor of what I'm working on! University of Maryland Fairness in AI Seminar, Penn State AI for Social Impact Seminar, USC CAIS Symposium joint keynote (with Patrick Fowler)

  • Recording of an interview with Jay Kanzler on KTRS where I talk about search, bias, algorithms, and society.

  • I talked about machine learning for credit risk on a techemergence podcast.

  • Videos of a session in which I gave the second talk and interview I gave on prediction markets at the Microsoft Research Faculty Summit are online (along with a ton of other interesting talks and interviews!)

  • The Wikimedia research newsletter of September 2013 discussed some of our work on manipulation in Wikipedia

  • An INFORMS Daily Report blog post from 2008 on some of our Wikipedia research

  • An article from The Economist in 2003, describing some of my research on modeling financial markets

  • Current Ph.D. Students and Postdocs

  • Amanda Kube (at WashU, co-advised with Patrick Fowler)
  • Andrew Estornell (at WashU, co-advised with Eugene Vorobeychik)
  • Tasfia Mashiat (at GMU, co-advised with Huzefa Rangwala)
  • Nabit Bajwa (at GMU)
  • Gaurab Pokharel (at GMU)
  • Former Ph.D. Students and Postdocs

  • Sujoy Sikdar (postdoc) → Asst. Prof. at Binghamton
  • Hao Yan (Ph.D. WashU 2019) → Facebook
  • Zhuoshu Li (Ph.D. WashU 2018) → Google
  • Mithun Chakraborty (Ph.D. WashU 2017) → Postdoc at NUS → Research Scientist at Michigan
  • Allen Lavoie (Ph.D, WashU 2016) → Google Brain
  • Meenal Chhabra (Ph.D., VT 2014) → Square, Inc.
  • Selected Service and Organization


    ACM SIGAI Chair (2019--); Vice-Chair (2013-2019)
    IFAAMAS Board Member (2018-2024)
    ACM TEAC Associate Editor (2018-)
    JAIR Associate Editor (2019-)
    IJCAI Sister Track Co-Chair 2015; Area Chair 2021; Senior PC 2019, 2018, 2016, 2013, 2011.
    AAMAS Program Co-Chair 2017; Sponsorships Co-Chair 2013; Track Chair 2021; Senior PC 2012, 2018; PC 2013-2015.
    ACM EC Workshops Chair 2011; Senior PC 2018; PC 2019, 2016, 2012-2014.
    AAAI Area Chair 2021, 2020, 2018, Senior PC 2019, 2016, 2012-2014; PC 2015
    NetEcon PC 2017.
    AMMA PC Co-Chair 2009; General Co-Chair 2011; PC 2015.
    ICML PC 2012, 2016.
    NeurIPS Reviewer 2012.
    ICDM PC 2008-10, 2012.
    KDD PC 2009.
    SDM PC 2008


    SIGAI Career Network Conference 2015, 2016
    AMMA 2009 and 2011 (plus Steering Committee)
    2008 RPI CS Day on Machine Learning and Data Mining